A note on transgenerational epigenetics affecting egg quality traits in meat-type quail.

1. The aim of the following experiment was to estimate transgenerational epigenetic variance for egg quality traits using genealogical and phenotypic information in meat-type quail. Measured traits included egg length (EL) and width (EWD), albumen weight (AW), shell weight (SW), yolk weight (YW) and egg weight (EW). 2. A total of 391 birds were evaluated for egg quality by collecting a sample of one egg per bird, during three consecutive days, starting on the 14th d of production. Analyses were performed using mixed models including the random epigenetic effect. Variance components were estimated by the restricted maximum likelihood method. A grid-search for values for the auto-recursive parameter (λ) was used in the variance components estimation. This parameter is directly related to the reset (v) and epigenetic transmissibility (1 - v) coefficients. 3. The epigenetic effect was not significant for any of the egg quality traits evaluated. Direct heritability estimates for egg quality traits ranged in magnitude from 0.06 to 0.33, whereby the higher estimates were found for AW and SW. Epigenetic heritability estimates were low and close to zero (ranging from 0.00 to 0.07) for all evaluated traits. 4. The current breeding strategies accounting for additive genetic effect seem to be suitable for egg quality traits in meat-type quail.

Transgenerational epigenetic variance for body weight in meat quails.

We aimed to estimate transgenerational epigenetic variance for body weight using genealogical and phenotypic information in meat quails. Animals were individually weighted from 1 week after hatching, with weight records at 7, 14, 21, 28, 35 and 42 days of age (BW7, BW14, BW21, BW28, BW35 and BW42, respectively). Single-trait genetic analyses were performed using mixed models with random epigenetic effects. Variance components were estimated by the restricted maximum likelihood method. A grid search for values of autorecursive parameter (λ) ranging from 0 to 0.5 was used in the variance component estimation. This parameter is directly related to the reset coefficient (ν) and the epigenetic coefficient of transmissibility (1-ν). The epigenetic effect was only significant for BW7. Direct heritability estimates for body weight ranged in magnitude (from 0.15 to 0.26), with the highest estimate for BW7. Epigenetic heritability was 0.10 for BW7, and close to zero for the other body weights. The inclusion of the epigenetic effect in the model helped to explain the residual and non-Mendelian variability of initial body weight in meat quails.

Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model.

We report a genomic selection (GS) study of growth and wood quality traits in an outbred F2 hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.

Selection index using the graphical area applied to sugarcane breeding.

This study aimed to develop a multivariate selection index based on the graphical area of a polygon formed by standardized values, also known as radar chart. This methodology may be used to assist selection of superior genotypes in sugarcane breeding programs. Seven technological traits in 37 sugarcane genotypes were evaluated. An area index (AI) was constructed and the resulting polygon areas were used to rank genotypes under selection. In this study, we propose the use of restricted maximum likelihood to estimate genetic parameters and mixed model equations to predict genotypic and breeding values. The area of each polygon was calculated for phenotypic, genotypic, and estimated breeding values. Thereby, the genotypes with larger area can be selected based on a detailed a posteriori evaluation of the radar charts. The proposed AI can be adjusted based on the breeders' specific interests, it is perfectly useful in other crops, and may also be applied to studies on genotype-environment interactions. Moreover, AI is a powerful tool that can evaluate trait stability of genotypes based on slight differences in the area formed by each genotype. Hence, this method is easy to apply and shows great potential for use in sugarcane breeding programs as well as in other breeding programs.